# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Relevance AI Endpoints Fal AI API
  version: 1.0.0
extends: openapi/relevance-ai-fal-ai-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-09-26'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 3
- target: $.paths['/fal_ai/categories'].get
  update:
    x-apievangelist-phrasing:
      intent: List fal.ai model categories
      effect: read
      questions:
      - What categories of fal.ai models are available?
      - Which kinds of fal.ai models can I group by, like image or video generation?
      instructions:
      - text: List all fal.ai model categories.
      - text: Show me the fal.ai category names I can filter models by.
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fal_ai/models'].get
  update:
    x-apievangelist-phrasing:
      intent: Browse available fal.ai models
      effect: read
      questions:
      - Which fal.ai models can my Relevance AI agents call?
      - Can I search fal.ai models by name and page through the results?
      instructions:
      - text: Search fal.ai models for {search}.
        slots:
          search: query.search
      - text: List fal.ai models in the {category} category, {limit} at a time.
        slots:
          category: query.category
          limit: query.limit
      method: generated
      generated: '2026-09-26'
- target: $.paths['/fal_ai/models/schema'].get
  update:
    x-apievangelist-phrasing:
      intent: Get the input schema of a fal.ai model
      effect: read
      questions:
      - What parameters does a particular fal.ai model accept?
      - Where do I find the input schema for a fal.ai model endpoint?
      instructions:
      - text: Show me the input schema for fal.ai endpoint {endpoint_id}.
        slots:
          endpoint_id: query.endpoint_id
      - text: Fetch the inputs model {endpoint_id} expects.
        slots:
          endpoint_id: query.endpoint_id
      method: generated
      generated: '2026-09-26'